Your ideal customers already ask ChatGPT, Gemini, Claude and Perplexity about you. Famascope shows what each of them is told, who they are sent to instead, and builds the stories that bring the right people closer to your brand.
Gemini names the brand less often than the other engines, and the gap is significant. Next step: the 3 sources Gemini cites most.
Measured in the answers of the assistants your buyers use, and in the visits they send
Every brand exists for a few kinds of customer. Each of them asks AI different questions, in different words, at different moments. Famascope starts from those people, not from the brand: what they ask, what they hear today, who they are sent to, and the story that would bring them to you. Then it helps you build that story where the AI will find it.
Runs SEO in-house, has to justify every new budget line to the board.
“Which agencies can audit how ChatGPT describes our brand?”
Three agencies named, a rival recommended, your brand mentioned last.
Proof on brands like theirs, a clear method, a number they can take to the board.
A case study with results, cited by the sources AI trusts, measured again next quarter.
Which agencies can audit how ChatGPT describes our brand?
Found in 3 of 4 engines. A rival is chosen. Missing proof: case studies.
Is optimising for AI answers worth it for a company our size?
Found and chosen in 2 of 4. Objection raised: unclear return.
Who can help us show up in AI answers in Spain?
Not found anywhere. A content gap goes straight to the plan.
An audit is only the first page. Every answer we collect becomes a line in a plan: what to write, where, how, and for whom. Your website is at the centre. Then the story travels everywhere your buyers listen.
We ask the AI assistants your buyers’ real questions, persona by persona, and read every answer: who is recommended, what is said about you, which sources it trusts. We add what your site, Google Analytics and Search Console already know.
Every gap becomes a decision with an owner: a page to write, a claim to prove, a source to win, a wrong statement to correct. Each one tied to the personas it serves and the number it should move.
The website comes first, because it is what AI reads most closely. Then the same story goes out through video, social, creators, digital PR and paid media, and we measure again to see what moved.
What the audit shows
Which questions your pages answer and which they miss, what AI crawlers can read, which claims need proof, and how each persona hears you today.
What changes
Pages to create and rewrite, in the words your buyers use. What is written and how: tone, claims, proof, comparisons and FAQs, persona by persona, with structured data that names you clearly.
The core is and stays your visibility and reputation in AI answers and AI search. Channels carry the story further. Product, marketing and offline decisions are a bonus: they come with the same data.
Six views of the same brand, connected. Every finding links to the answers behind it, and every task links back to the finding.
The client at a glance: the four numbers, how they moved since the last run, the rivals that win the answer and the next step.
Each persona carries its own questions, its own rivals and its own numbers. Strategy, content and paid search are planned person by person.
Prompt tracking across engines, run after run: which questions name the brand, which pages get cited, and where rivals take the answer.
Pages are fetched and parsed by code, compared with your crawl and with what an AI reads. Nothing is reported as missing unless it really is.
Google Analytics and Search Console inside the same view: what AI assistants send to the site, how it compares with search and paid, and which pages are already being worked on.
Actions from every strategy become tasks with evidence, owners, client dependencies and dates. A task is verified only when the next run shows the change.
An AI can name a brand and still recommend someone else. Famascope follows each answer all the way, from a mention to a choice the buyer can trust.
Sample data. Engines are measured one by one, because they rarely agree.
Fama, malum qua non aliud velocius ullum.
Fama: no other evil travels faster. Virgil, Aeneid IV, 174
From fari, to speak. What is said about someone: report, rumour, renown, reputation.
From skopein, to look at closely, to examine.
An instrument to observe what AI says about a brand, and to shape what it says next.
Fama starts small, then walks the earth with her head in the clouds. Under every one of her feathers there is a watchful eye, a tongue, a speaking mouth and a listening ear. She carries truth and invention with the same conviction.
Ovid gives her a house at the centre of the world, between land, sea and sky. It has a thousand openings and no doors, it is open day and night, and its bronze walls echo whatever they hear. Stories arrive, grow as they are retold, and leave in new versions.
AI assistants read what the web says about a brand and retell it to millions of people, in their own words, every day. Some of it is accurate. Some is out of date, incomplete or about somebody else. Most brands have never heard it.
Fama travels on feathers, so the mark is one. Reputation is a story, and AI is now one of its authors.
The solid vane is what is already said about you, in every answer the assistants give today.
The mint barbs are the plan: what you improve, manage and grow next.
The areas as they stand in October 2026. They will grow and change before release.
Where the brand stands, what changed since the last run, and what to do next.
Traffic, leads and sales from AI assistants, Google and paid search, side by side.
One profile per buyer, measured over time: what they ask, who wins them, what they need to hear and which audiences to target.
A fast pre-audit of how AI describes the brand, ready before the first meeting.
What to fix, say and prove so the AI tells a better story.
A brief signed with the client, then a measured study of attributes, rivals, claims and objections.
Findings turned into priorities with owners, KPIs and a date for the next run.
Prompt tracking across engines: which questions name the brand and which pages get cited.
Pages to create, update and connect, chosen from the questions the brand loses.
Real page fetches, crawl data and AI bot tests, compared page by page.
A living plan of technical, content and entity fixes, scoped by template.
Tasks with evidence, owners, client dependencies and a timeline. Each one checked again at the next run, so done means done.
The name holds the method. Four steps, the same for every brand, repeated every quarter, always starting from people.
Start from the buyers: the personas a brand exists for, their needs, their expectations and the questions they ask AI.
In Famascope: Personas, the signed brief
Measure how AI assistants describe the brand, its products and its place in the market, persona by persona and engine by engine.
In Famascope: Brand perception, full study, Visibility
Find what holds the brand back and rank it: barriers for AI crawlers, missing content, lost questions, weak sources, stories nobody tells.
In Famascope: Site audit, strategies, action plans
Deliver the plan, track the prompts, and check every change at the next run and in Google Analytics and Search Console.
In Famascope: Delivery, Performance
Famascope is built by Fabio Granata, who has worked in search and digital marketing since 2008: directory advertising first, then paid search, SEO, affiliate and paid social, and now generative search.
Almost two decades of watching how people look for things, and how the tools that answer them keep changing. The software is the visible part. Underneath it is a way of working: how questions are chosen, how answers are judged, when a difference is real and when it is noise, and how a finding becomes a task that someone completes and checks.
The first brand Famascope works on is its founder’s own. It is the most demanding client, and the most honest case study.
Until then Famascope is in private use. This page will change as the product grows. The idea behind it will not.
Proof of concept, built and tested privately on real brands.
In use with consulting clients. The method refined, the first case studies written.
Public release for brands and agencies, alongside consulting.
A platform and a method for AI brand perception. It measures what AI assistants say about a brand, to which buyers, and based on which sources, then turns the findings into a plan and tracks the work until the next measurement.
The public release is planned for 2028. Until then Famascope is used privately, on real brands, alongside consulting work. If you want to know what AI says about your brand before then, write to us.
Today the answers of ChatGPT, Gemini, Claude and Perplexity are measured directly. Visits from these and other assistants, such as Copilot, DeepSeek, Meta AI, Mistral and Grok, are read from Google Analytics. The list will grow as the assistants people use change.
Because AI does not answer brands, it answers people. A founder and a head of SEO ask different questions and hear different answers about the same company. Measuring a brand on average hides who it is winning and who it is losing. Famascope measures, plans and reports persona by persona.
Both. The software does the measuring, the checking and the tracking. The method decides which questions matter, how answers are judged and what the brand should do about them.
No. Search still matters, and AI assistants often build their answers on the same pages search engines rank. Famascope puts search, AI visibility and paid search side by side, so the work on one supports the others.
Clients own their data. Google Analytics and Search Console are read only, never sold, never used for advertising and never sent to AI model providers. The privacy policy has the details.
Famascope is in private use, but the method is already at work. Join the early access list, or write and tell us about your brand.